One of the most promising new technologies, is the use of big data analytics coupled with artificial intelligence. The concept is to use the power of computing to allow for decision making that could be as good (or ideally better) than the decisions made by a human operator. There are many places that this is being applied from robotics to autonamous vehicles.

There is also the potential to apply these concepts to enhance the operation and control of buildings and homes. One application for control is what is referred to as “Model Predictive Control” (MPC) which uses calculations that could include historical performance, algorithms, and other data to provide for better control. Today most of our control systems operate using a certain level of error or imprecision. The most accurate control (such as PID) try to minimize this inaccuracy. MPC has the potential to provide for more accurate control as well as optimized operation. For example one current research project is attempting to control a fans energy use at the limits of the fan curve and reduce the error that exists with the use of conventional “trim and responsible” control.

While these new concepts show great potential, they are also generally more complicated and computationally intensive than what they replace. As computing power get cheaper and programming tools get easier, it will likely be broadly adopted. We would anticipate that the first application may be embedded in equipment, since there is enough volume to justify the added costs to develop the strategy. In time it will be more broadly used across building control systems. In the meantime it is a good time to learn about the technology and what it can and can’t do.